Gene Expression Noise Produces Cell-to-Cell Heterogeneity in Eukaryotic Homologous Recombination Rate

Genomic and metabolic instability during long-term fermentation of an industrial Saccharomyces cerevisiae strain engineered for C5 sugar utilization

The genetic stability and metabolic robustness of production strains is one of the key criteria for the production of bio-based products by microbial fermentation on an industrial scale. These criteria were here explored in an industrial ethanol-producer strain of Saccharomyces cerevisiae able to co-ferment D-xylose and L-arabinose with glucose through the chromosomal integration of several copies of pivotal genes for the use of these pentose (C5) sugars. Using batch sequential cultures in a controlled bioreactor that mimics long-term fermentation in an industrial setting, this strain was found to exhibit significant fluctuations in D-xylose and L-arabinose consumption as early as the 50th generation and beyond. These fluctuations seem not related to the few low-consumption C5 sugar clones that appeared throughout the sequential batch cultures at a frequency lower than 1.5% and that were due to the reduction in the number of copies of transgenes coding for C5 sugar assimilation enzymes. Also, subpopulations enriched with low or high RAD52 expression, whose expression level was reported to be proportional to homologous recombination rate did not exhibit defect in C5-sugar assimilation, arguing that other mechanisms may be responsible for copy number variation of transgenes. Overall, this work highlighted the existence of genetic and metabolic instabilities in an industrial yeast which, although modest in our conditions, could be more deleterious in harsher industrial conditions, leading to reduced production performance.

Tracing back primed resistance in cancer via sister cells

Exploring non-genetic evolution of cell states during cancer treatments has become attainable by recent advances in lineage-tracing methods. However, transcriptional changes that drive cells into resistant fates may be subtle, necessitating high resolution analysis. Here, we present ReSisTrace that uses shared transcriptomic features of sister cells to predict the states priming treatment resistance. Applying ReSisTrace in ovarian cancer cells perturbed with olaparib, carboplatin or natural killer (NK) cells reveals pre-resistant phenotypes defined by proteostatic and mRNA surveillance features, reflecting traits enriched in the upcoming subclonal selection. Furthermore, we show that DNA repair deficiency renders cells susceptible to both DNA damaging agents and NK killing in a context-dependent manner. Finally, we leverage the obtained pre-resistance profiles to predict and validate small molecules driving cells to sensitive states prior to treatment. In summary, ReSisTrace resolves pre-existing transcriptional features of treatment vulnerability, facilitating both molecular patient stratification and discovery of synergistic pre-sensitizing therapies.

Emergent dynamics of underlying regulatory network links EMT and androgen receptor-dependent resistance in prostate cancer

Advanced prostate cancer patients initially respond to hormone therapy, be it in the form of androgen deprivation therapy or second-generation hormone therapies, such as abiraterone acetate or enzalutamide. However, most men with prostate cancer eventually develop hormone therapy resistance. This resistance can arise through multiple mechanisms, such as through genetic mutations, epigenetic mechanisms, or through non-genetic pathways, such as lineage plasticity along epithelial-mesenchymal or neuroendocrine-like axes. These mechanisms of hormone therapy resistance often co-exist within a single patient's tumor and can overlap within a single cell. There exists a growing need to better understand how phenotypic heterogeneity and plasticity results from emergent dynamics of the regulatory networks governing androgen independence. Here, we investigated the dynamics of a regulatory network connecting the drivers of androgen receptor (AR) splice variant-mediated androgen independence and those of epithelial-mesenchymal transition. Model simulations for this network revealed four possible phenotypes: epithelial-sensitive (ES), epithelial-resistant (ER), mesenchymal-resistant (MR) and mesenchymal-sensitive (MS), with the latter phenotype occurring rarely. We observed that well-coordinated "teams" of regulators working antagonistically within the network enable these phenotypes. These model predictions are supported by multiple transcriptomic datasets both at single-cell and bulk levels, including in vitro EMT induction models and clinical samples. Further, our simulations reveal spontaneous stochastic switching between the ES and MR states. Addition of the immune checkpoint molecule, PD-L1, to the network was able to capture the interactions between AR, PD-L1, and the mesenchymal marker SNAIL, which was also confirmed through quantitative experiments. This systems-level understanding of the driver of androgen independence and EMT could aid in understanding non-genetic transitions and progression of such cancers and help in identifying novel therapeutic strategies or targets.

Non-genetic resistance facilitates survival while hindering the evolution of drug resistance due to intraspecific competition

Rising rates of resistance to antimicrobial drugs threaten the effective treatment of infections across the globe. Drug resistance has been established to emerge from non-genetic mechanisms as well as from genetic mechanisms. However, it is still unclear how non-genetic resistance affects the evolution of genetic drug resistance. We develop deterministic and stochastic population models that incorporate resource competition to quantitatively investigate the transition from non-genetic to genetic resistance during the exposure to static and cidal drugs. We find that non-genetic resistance facilitates the survival of cell populations during drug treatment while hindering the development of genetic resistance due to competition between the non-genetically and genetically resistant subpopulations. Non-genetic resistance in the presence of subpopulation competition increases the fixation times of drug resistance mutations, while increasing the probability of mutation before population extinction during cidal drug treatment. Intense intraspecific competition during drug treatment leads to extinction of susceptible and non-genetically resistant subpopulations. Alternating between drug and no drug conditions results in oscillatory population dynamics, increased resistance mutation fixation timescales, and reduced population survival. These findings advance our fundamental understanding of the evolution of resistance and may guide novel treatment strategies for patients with drug-resistant infections.

Multiple Stochastic Parameters Influence Genome Dynamics in a Heterozygous Diploid Eukaryotic Model

The heterozygous diploid genome of Candida albicans displays frequent genomic rearrangements, in particular loss-of-heterozygosity (LOH) events, which can be seen on all eight chromosomes and affect both laboratory and clinical strains. LOHs, which are often the consequence of DNA damage repair, can be observed upon stresses reminiscent of the host environment, and result in homozygous regions of various sizes depending on the molecular mechanisms at their origins. Recent studies have shed light on the biological importance of these frequent and ubiquitous LOH events in C. albicans. In diploid Saccharomyces cerevisiae, LOH facilitates the passage of recessive beneficial mutations through Haldane’s sieve, allowing rapid evolutionary adaptation. This also appears to be true in C. albicans, where the full potential of an adaptive mutation is often only observed upon LOH, as illustrated in the case of antifungal resistance and niche adaptation. To understand the genome-wide dynamics of LOH events in C. albicans, we constructed a collection of 15 strains, each one carrying a LOH reporter system on a different chromosome arm. This system involves the insertion of two fluorescent marker genes in a neutral genomic region on both homologs, allowing spontaneous LOH events to be detected by monitoring the loss of one of the fluorescent markers using flow cytometry. Using this collection, we observed significant LOH frequency differences between genomic loci in standard laboratory growth conditions; however, we further demonstrated that comparable heterogeneity was also observed for a given genomic locus between independent strains. Additionally, upon exposure to stress, three outcomes could be observed in C. albicans, where individual strains displayed increases, decreases, or no effect of stress in terms of LOH frequency. Our results argue against a general stress response triggering overall genome instability. Indeed, we showed that the heterogeneity of LOH frequency in C. albicans is present at various levels, inter-strain, intra-strain, and inter-chromosomes, suggesting that LOH events may occur stochastically within a cell, though the genetic background potentially impacts genome stability in terms of LOH throughout the genome in both basal and stress conditions. This heterogeneity in terms of genome stability may serve as an important adaptive strategy for the predominantly clonal human opportunistic pathogen C. albicans, by quickly generating a wide spectrum of genetic variation combinations potentially permitting subsistence in a rapidly evolving environment.

Mutational sources of trans-regulatory variation affecting gene expression in Saccharomyces cerevisiae

Heritable variation in a gene’s expression arises from mutations impacting cis- and trans-acting components of its regulatory network. Here, we investigate how trans-regulatory mutations are distributed within the genome and within a gene regulatory network by identifying and characterizing 69 mutations with trans-regulatory effects on expression of the same focal gene in Saccharomyces cerevisiae. Relative to 1766 mutations without effects on expression of this focal gene, we found that these trans-regulatory mutations were enriched in coding sequences of transcription factors previously predicted to regulate expression of the focal gene. However, over 90% of the trans-regulatory mutations identified mapped to other types of genes involved in diverse biological processes including chromatin state, metabolism, and signal transduction. These data show how genetic changes in diverse types of genes can impact a gene’s expression in trans, revealing properties of trans-regulatory mutations that provide the raw material for trans-regulatory variation segregating within natural populations.

Interplay between genetic, epigenetic, and gene expression variability: Considering complexity in evolvability

Genetic variability, epigenetic variability, and gene expression variability (noise) are generally considered independently in their relationship with phenotypic variation. However, they appear to be intrinsically interconnected and influence it in combination. The study of the interplay between genetic and epigenetic variability has the longest history. This article rather considers the introduction of gene expression variability in its relationships with the two others and reviews for the first time experimental evidences over the four relationships connected to gene expression noise. They show how introducing this third source of variability complicates the way of thinking evolvability and the emergence of biological novelty. Finally, cancer cells are proposed to be an ideal model to decipher the dynamic interplay between genetic, epigenetic, and gene expression variability when one of them is either experimentally increased or therapeutically targeted. This interplay is also discussed in an evolutionary perspective in the context of cancer cell drug resistance.

Coupled Feedback Loops Involving PAGE4, EMT and Notch Signaling Can Give Rise to Non-genetic Heterogeneity in Prostate Cancer Cells

Non-genetic heterogeneity is emerging as a crucial factor underlying therapy resistance in multiple cancers. However, the design principles of regulatory networks underlying non-genetic heterogeneity in cancer remain poorly understood. Here, we investigate the coupled dynamics of feedback loops involving (a) oscillations in androgen receptor (AR) signaling mediated through an intrinsically disordered protein PAGE4, (b) multistability in epithelial-mesenchymal transition (EMT), and c) Notch-Delta-Jagged signaling mediated cell-cell communication, each of which can generate non-genetic heterogeneity through multistability and/or oscillations. Our results show how different coupling strengths between AR and EMT signaling can lead to monostability, bistability, or oscillations in the levels of AR, as well as propagation of oscillations to EMT dynamics. These results reveal the emergent dynamics of coupled oscillatory and multi-stable systems and unravel mechanisms by which non-genetic heterogeneity in AR levels can be generated, which can act as a barrier to most existing therapies for prostate cancer patients.

Characterization of systemic genomic instability in budding yeast

Conventional models of genome evolution are centered around the principle that mutations form independently of each other and build up slowly over time. We characterized the occurrence of bursts of genome-wide loss-of-heterozygosity (LOH) in Saccharomyces cerevisiae, providing support for an additional nonindependent and faster mode of mutation accumulation. We initially characterized a yeast clone isolated for carrying an LOH event at a specific chromosome site, and surprisingly found that it also carried multiple unselected rearrangements elsewhere in its genome. Whole-genome analysis of over 100 additional clones selected for carrying primary LOH tracts revealed that they too contained unselected structural alterations more often than control clones obtained without any selection. We also measured the rates of coincident LOH at two different chromosomes and found that double LOH formed at rates 14- to 150-fold higher than expected if the two underlying single LOH events occurred independently of each other. These results were consistent across different strain backgrounds and in mutants incapable of entering meiosis. Our results indicate that a subset of mitotic cells within a population can experience discrete episodes of systemic genomic instability, when the entire genome becomes vulnerable and multiple chromosomal alterations can form over a narrow time window. They are reminiscent of early reports from the classic yeast genetics literature, as well as recent studies in humans, both in cancer and genomic disorder contexts. The experimental model we describe provides a system to further dissect the fundamental biological processes responsible for punctuated bursts of structural genomic variation.

SIR2 Expression Noise Can Generate Heterogeneity in Viability but Does Not Affect Cell-to-Cell Epigenetic Silencing of Subtelomeric URA3 in Yeast

Chromatin structure clearly modulates gene expression noise, but the reverse influence has never been investigated, namely how the cell-to-cell expression heterogeneity of chromatin modifiers may generate variable rates of epigenetic modification. Sir2 is a well-characterized histone deacetylase of the Sirtuin family. It strongly influences chromatin silencing, especially at telomeres, subtelomeres and rDNA. This ability to influence epigenetic landscapes makes it a good model to study the largely unexplored interplay between gene expression noise and other epigenetic processes leading to phenotypic diversification. Here, we addressed this question by investigating whether noise in the expression of SIR2 was associated with cell-to-cell heterogeneity in the frequency of epigenetic silencing at subtelomeres in Saccharomyces cerevisiae Using cell sorting to isolate subpopulations with various expression levels, we found that heterogeneity in the cellular concentration of Sir2 does not lead to heterogeneity in the epigenetic silencing of subtelomeric URA3 between these subpopulations. We also noticed that SIR2 expression noise can generate cell-to-cell variability in viability, with lower levels being associated with better viability. This work shows that SIR2 expression fluctuations are not sufficient to generate cell-to-cell heterogeneity in the epigenetic silencing of URA3 at subtelomeres in Saccharomyces cerevisiae but can strongly affect cellular viability.

Synthetic Pesticides Used in Agricultural Production Promote Genetic Instability and Metabolic Variability in Candida spp

The effects of triazole fungicide Tango^® (epoxiconazole) and two neonicotinoid insecticide formulations Mospilan^® (acetamiprid) and Calypso^® (thiacloprid) were investigated in Candida albicans and three non-albicans species Candida pulcherrima, Candida glabrata and Candida tropicalis to assess the range of morphological, metabolic and genetic changes after their exposure to pesticides. Moreover, the bioavailability of pesticides, which gives us information about their metabolization was assessed using gas chromatography-mass spectrophotometry (GC-MS). The tested pesticides caused differences between the cells of the same species in the studied populations in response to ROS accumulation, the level of DNA damage, changes in fatty acids (FAs) and phospholipid profiles, change in the percentage of unsaturated to saturated FAs or the ability to biofilm. In addition, for the first time, the effect of tested neonicotinoid insecticides on the change of metabolic profile of colony cells during aging was demonstrated. Our data suggest that widely used pesticides, including insecticides, may increase cellular diversity in the Candida species population-known as clonal heterogeneity-and thus play an important role in acquiring resistance to antifungal agents.